Interorganizational networks is a flourishing topic of research within public affairs, and yet, there is still a significant amount that is unknown about the ways in which networks function (Provan & Kenis, 2008; Popp et al., 2014). Therefore, this study explores how one particular aspect of a network, its governance, impacts network effectiveness. Using Provan and Kenis's (2008) theory on network effectiveness as a framework, the study asks: What type of network governance structures exist in public health collaboratives? What type of network governance structures lead to effective outcomes? How does governance interact with certain critical contingencies to explain effectiveness?;To address these questions, the study contains a secondary analysis of the PARTNER Dataset, as well as additional data collected during the PARTNER Manager Survey. A descriptive analysis was used to determine what type of governance structures existed within public health. Then, OLS was used to test how these structures impact effectiveness. Finally, the study tested how governance interacted with certain critical contingencies of networks (trust, size, goal consensus, and need for network level competencies) to impact effectiveness.;All three governance structures identified by Provan and Kenis (2008) were found to exist within the dataset, with Lead organization as the most common structure, followed by Shared governance, and then NAO governance. The study also found a statistically significant relationship between governance structures and effectiveness. However, the findings demonstrate little support for Provan and Kenis's theoretical propositions. While the governance structure variables were statistically significant and critical contingency variables were statistically significant in some instances, there was an overall lack of support for the interaction of critical contingency variables with governance to explain effectiveness. Finally, different measures of effectiveness resulted in inconsistent results for each model. This either indicates that a construct validity error, or that new measures of effectiveness need to be developed to reflected the complex and multi-faceted nature of the variable.;The study's findings provide evidence that network governance is an important variable in explaining network effectiveness. It can also provide practioners with insights on the most effective ways to govern networks. However, as this study has a small sample size, any generalizations about networks and their effectiveness should be made with extreme caution. Further, it demonstrates the need for a multi-theoretical model of network effectiveness.
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